Exact Confidence Interval Construction

and Test of Hypothesis for

The Binomial Populations

This site is a part of the JavaScript E-labs learning objects for decision making. Other JavaScript in this series are categorized under different areas of applications in the MENUsection on this page.

Enter the needed information, and then click the

Calculatebutton.In entering your data to move from cell to cell in the data-matrix use the

Tab keynot arrow or enter keys.

Application to the test of hypothesis:Notice that, one may utilize Confidence Interval (CI) for the test of hypothesis purposes. Suppose you wish to test the following general test of hypothesis:

HThe population parameter is almost equal to a given claimed value,_{0}:against the alternative:

HThe population parameter is not even close to the claimed value._{a}:The process of carrying the above test of hypothesis at a level of significance using CI is as follow:

- Ignore the claimed value in the null hypothesis, for time being.
- Construct a 100(1- a)% confidence interval based on the available data.
- If the constructed CI does not contain the claimed value, then there is enough evidence to reject the null hypothesis. Otherwise, there is no reason to reject the null hypothesis.

For Technical Details, Back to:

Statistical Thinking for Decision Making

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Professor Hossein Arsham

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